Can Crowdchecking Curb Misinformation? Evidence from Community Notes

To battle against rampant misinformation on social media, many platforms are experimenting with crowdsourced fact-checking—systems that rely on social media users’ annotations of potentially misleading content. This paper investigates the efficacy of such systems in curbing misinformation in the context of Community Notes, a pioneering crowdsourced fact-checking system from Twitter/X. Utilizing a regression discontinuity design, we empirically identified the positive effect of publicly displaying community notes on an author’s voluntary retraction of the noted tweet, demonstrating the viability of crowdsourced fact-checking as an alternative to professional fact-checking and forcible content removal. Our findings reveal that the effect is primarily driven by the author’s reputational concern and perceived social pressure, and there is considerable heterogeneity of such effect depending on specific tweet- and user-level characteristics. Platforms, therefore, can exploit the underlying mechanism and explore the use of contextual factors to harness the full potential of crowdsourced fact-checking. Furthermore, results from discrete-time survival analyses show that publicly displaying community notes not only increases the probability of tweet retractions but also, accelerates the retraction process among retracted tweets, thereby improving platforms’ responsiveness to curb misinformation. This study offers important insights to both social media platforms and policymakers on the promise of crowdsourced fact-checking and calls for the broad participation of social media users to collectively tackle the problem of misinformation.

History: Ravi Bapna, Senior Editor; Anuj Kumar, Associate Editor.

Funding: Y. Gao was supported by the Gies Grant 2023 from the Gies College of Business University of Illinois Urbana-Champaign.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2024.1609.